|
| 1 | +from itertools import batched |
| 2 | +from pathlib import Path |
| 3 | +from typing import Annotated |
| 4 | + |
| 5 | +from annotated_types import Ge |
| 6 | +import djclick as click |
| 7 | +from isic_metadata.metadata import MetadataRow |
| 8 | +import pyarrow as pa |
| 9 | +import pyarrow.parquet as pq |
| 10 | +from pydantic_to_pyarrow import get_pyarrow_schema |
| 11 | + |
| 12 | +from isic.core.models import Image |
| 13 | + |
| 14 | +ROW_GROUP_SIZE = 10_000 |
| 15 | + |
| 16 | + |
| 17 | +class ParquetMetadataRow(MetadataRow): |
| 18 | + age_approx: Annotated[int, Ge(0)] | None = None |
| 19 | + |
| 20 | + |
| 21 | +@click.command(help="Export the metadata for a set of images to a parquet file") |
| 22 | +@click.argument("parquet_path", type=str) |
| 23 | +@click.option("--public", is_flag=True, default=True) |
| 24 | +def export_metadata_parquet(parquet_path: str, *, public: bool = True): |
| 25 | + """Export the metadata for a set of images to a parquet file.""" |
| 26 | + output_path = Path(parquet_path) |
| 27 | + schema = get_pyarrow_schema(ParquetMetadataRow, exclude_fields=True) |
| 28 | + |
| 29 | + for field in ["age", "marker_pen", "blurry", "hairy", "color_tint"]: |
| 30 | + schema = schema.remove(schema.get_field_index(field)) |
| 31 | + |
| 32 | + rows = ( |
| 33 | + ParquetMetadataRow(**image.metadata) |
| 34 | + for image in Image.objects.filter(public=public).select_related("accession").iterator() |
| 35 | + ) |
| 36 | + |
| 37 | + with pq.ParquetWriter(output_path, schema) as writer: |
| 38 | + for batch in batched(rows, ROW_GROUP_SIZE): |
| 39 | + row_dicts = [row.model_dump(mode="python") for row in batch] |
| 40 | + table = pa.Table.from_pylist(row_dicts, schema=schema) |
| 41 | + writer.write_table(table) |
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